Rahman , A. and Roy, M. P. and Raina, A. K. and Singh, N. and Rukhayar, S. and Mishra , A. K. (2025) Prediction of Blast Induced Ground Vibration in Deccan Trap Volcanic Rock at Ulwe Hill, New Mumbai Airport: Evaluation Based on Empirical, ANN and Multiple Machine Learning Models. MAPAN-Journal of Metrology Society of India. ISSN 0970-3950

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Abstract

Blasting is a conventional method of rock breakage in mines and civil works. Ground vibration are integral part of a blast and lot of the studies have been done by umpteen researchers with the aim to mitigate the impact of ground vibrations on nearby structures, particularly not belonging to the owner of the mine or civil works. However, owing to variations in geology, explosive and blast design, spatial attenuation of the ground vibration is site specific. This study relates to a detailed analysis of data of 107 blasts acquired from, under construction, New Navi Mumbai airport site. The data was analyzed and evaluated over general regression and ANN based models, characterized by Mean Square Error (MSE), Root Mean Square Error (RMSE), Mean Absolute Error (MAE), Correlation of Determination (R 2 ), Correlation Coefficient (R), and Nash–Sutcliffe Model Efficiency Coefficient (NASH). Out of 9 models, it was found that Gradient Boosting Regression model yielded the minimum MSE, RMSE, MAE and best R 2 , R and NASH, i.e., 0.11, 0.34, 0.23, 0.51and 0.91, 0.95, 0.91 respectively

Item Type:	Article
Uncontrolled Keywords:	Civil blasting; Ground vibration; Maximum charge per delay; Vibration prediction; ANN; Machine learning
Subjects:	Blasting
Divisions:	UNSPECIFIED
Depositing User:	Mr. B. R. Panduranga
Date Deposited:	19 Dec 2025 05:04
Last Modified:	19 Dec 2025 05:05
URI:	https://cimfr.csircentral.net/id/eprint/2908

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